# GPT-3.5-turbo vs Trinity Large Thinking

> Trinity Large Thinking is the stronger model overall, scoring 38.1 to 23.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-3-5-turbo-vs-trinity-large-thinking
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and Trinity Large Thinking in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Trinity Large Thinking leads 40.3 to 10.0.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.50 / $1.50 for GPT-3.5-turbo.
- Trinity Large Thinking accepts more context: 262K tokens versus 16K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 23.1 | 38.1 |
| Rank | 345 | 180 |
| Context | 16K | 262K |
| Input $/M | $0.50 | $0.25 |
| Output $/M | $1.50 | $0.80 |
| Weights | Proprietary | Open |

## Coding

- GPT-3.5-turbo: 23.5 (#326)
- Trinity Large Thinking: 33.8 (#238)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1137 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 3.5% | — |
| BigCodeBench Instruct | 39.1% | — |
| BigCodeBench Complete | 50.6% | — |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |

## Agentic & Tool Use

- GPT-3.5-turbo: —
- Trinity Large Thinking: —

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| METR Time Horizons | 21.5% | — |

## Reasoning

- GPT-3.5-turbo: 13.3 (#328)
- Trinity Large Thinking: 16.3 (#298)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1108 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 41.6% |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Surface Evolver Bench | — | 15.6% |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| Epoch Capabilities Index | 118.48 | — |
| ForecastBench | 50.4 | — |
| WinoGrande | 81.6% | — |

## Math

- GPT-3.5-turbo: 6.0 (#321)
- Trinity Large Thinking: 34.9 (#149)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1142 | 1366 |
| FrontierMath (Tiers 1-3) | 0% | — |
| OTIS Mock AIME 2024-2025 | 2.2% | — |
| MATH Level 5 | 15.9% | — |
| GSM8K | 57.8% | — |

## Knowledge

- GPT-3.5-turbo: 10.0 (#298)
- Trinity Large Thinking: 40.3 (#107)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1070 | 1359 |
| GPQA Diamond | 28% | — |
| Vectara Hallucination Rate | — | 6.9% |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |

## Multilingual

- GPT-3.5-turbo: 31.6 (#253)
- Trinity Large Thinking: 46.4 (#155)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1108 | 1325 |
| LMArena Chinese | 1075 | 1372 |
| LMArena French | 1117 | 1374 |
| LMArena German | 1090 | 1356 |
| LMArena Japanese | 1043 | 1312 |
| LMArena Korean | 1019 | 1304 |
| LMArena Russian | 1123 | 1338 |
| LMArena Spanish | 1120 | 1356 |

## Instruction Following

- GPT-3.5-turbo: 58.1 (#257)
- Trinity Large Thinking: 70.7 (#157)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1119 | 1334 |

## Long Context

- GPT-3.5-turbo: 34.0 (#249)
- Trinity Large Thinking: 41.2 (#139)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1121 | 1355 |

## Writing & Preference

- GPT-3.5-turbo: 25.4 (#300)
- Trinity Large Thinking: 54.0 (#152)

| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1125 | 1340 |
| LMArena Creative Writing | 1092 | 1321 |
| LMArena Multi-Turn | 1117 | 1342 |
| EQ-Bench Creative Writing | 451 | — |

## FAQ

### Is GPT-3.5-turbo better than Trinity Large Thinking?

Trinity Large Thinking is the stronger model overall, scoring 38.1 to 23.1 on the Noometry Index.

### Which is cheaper, GPT-3.5-turbo or Trinity Large Thinking?

Trinity Large Thinking is cheaper. It lists at $0.25 per million input tokens and $0.80 per million output tokens; GPT-3.5-turbo lists at $0.50 and $1.50.

### Is GPT-3.5-turbo or Trinity Large Thinking better for coding?

Trinity Large Thinking scores higher on coding benchmarks: 33.8 versus 23.5 in the Noometry coding category.

### Which has the bigger context window?

Trinity Large Thinking does, with 262K tokens against 16K.

### How many benchmarks do GPT-3.5-turbo and Trinity Large Thinking share?

17 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Trinity Large Thinking has 24.